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DNtegrAte: An Open-Source Python Package for Performing DNA Assemblies with the OT-2 Liquid Handling Robot

John Bryant, Mason Kellinger, Cameron Longmire, & R. Clay Wright   jbryant2@vt.edu   jbryantvt.github.io   github.com/PlantSynBio/opentrons

Abstract: DNA assembly is low throughput and unreliable. Implementation of DNA design software is usually done by hand which is low-throughput and error-prone. Here, we present an open-source python package to integrate DNA assembly software with the OT-2 liquid handling robot. Our package reduces the time, training, costs, and wastes associated with molecular biology. We demonstrate the flexibility and versatility of DNtegrAte by demonstrating PCRs and multipart assemblies.

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Introduction

The Troublesome Cloning Workflow

  • Extensive training and high error-rates are typical in synbio labs due to the complexity of the cloning workflow in practice.
  • Researchers spend more time and resources on executing the workflow rather than actually engineering biology.

Fig. 1: The Cloning Workflow - (A) Design constructs with existing software algorithms. (B) Amplify parts (C) Assemble new constructs (D) Maintain constructs in E. coli (E) Use for downstream applications.

Effective Assembly Demonstration

Fig. 2: Cloning with DNtegrAte - (A) DNtegrAte PCR protocol verified by successful amplification of fragments varying in length and annealing temp. (B) Graphical depiction of optimal annealing temp gradient calculated for 2A. (C) DNtegrAte IVA protocol verified by successful amplification of each assembly fragment. (D) Consistent transformation efficiency, correct antibiotic resistance, and correct chromoprotein expression further validate DNtegrAte IVA protocol.

Data and Methods

Software Design:

  • Protocol scripts are flexible and fully automated.
  • GUI for specifying parameters like template concentration, PCR volume, etc. is included.
  • Input and output files are automatically generated and archived in dated directories available at github.com/plantsynbio/opentrons.

Data Collection:

  • The multi-fragment PCR for gradient algorithm validation (fig 2A, 2B) was based on a design for an auxin signaling protein motif deletion.
  • The IVA for assembly protocol validation (fig 2C, 2D) was based on a chromoprotein swap design which assembles two backbone fragments from a blue plasmid with an Amp resistance fragment, and each color to produce products in fig 2D.